Abstract
This experiment is to demonstrate the effectiveness of CloudFlow – enabled Process Planning simulation/optimisation software to customised/high_- precision mechanical parts, leading to improved product quality, productivity and sustainability, and reduced IT investment requirements to facilitate SMEs. Industrial cases with complex machining Big Data will validate system´s scalability, reliability and customisation. An industrial demonstrator will support wider exploitation by European SMEs.
Technical/economic impacts
The dynamics of machining processes provide complex Big Data and test scenarios for CloudFlow. CloudFlow services’ scalability, performance, reliability, and service integration based on 4 real-world industrial case studies with a large quantity and variety of data will be evaluated.
Based on real-world cases, this experiment will verify and showcase the advantage of the cloudified CAPP and the power of computing/simulation by high-performance computing (HPC) in CloudFlow to enhance CAPP, including further improved process planning quality, lead time reduction for optimised process plan generation, Cloud technology benefits to SMEs by reducing their IT and support investments significantly, etc. The total number of simulation with different combination of process parameters and parts is planned as 19,000 times. For one simulation/optimisation of scheduling, sequencing, setup and G-codes of the three reference parts, the simulation time is estimated 2 CPUh.
Project:
Partners:
Coventry University -CU- (UK), Powerkut Ltd. -PKT- (UK), Arctur računalniški inženiring d.o.o. (Slovenia)
Sector
Machinery & equipment
Keywords
Modelling & Simulation
